Graphnet’s Elective Recovery tool within the Population Health Management platform supports trusts to validate, cleanse and manage lists. The Elective Recovery tool integrates waiting lists with data from across care settings to provide clinical and operational staff with a clearer, richer view of patients along the perioperative pathway, enabling them to optimise and prioritise waiting lists more effectively, clear bottlenecks in the system and monitor and ensure health equity.
1. Book appointments for all patients in the 78w cohort without a Decision To Admit (DTA):
The Elective Recovery tool enables the waiting list to be filtered by patient cohort supporting clinical and operational teams to focus on the 78w, non-admitted cohort. Within a few steps, operational teams can use the tool to rapidly categorise and validate the patients in this cohort, identify those who don’t have appointments booked and begin to work through a prioritised list. Once admitted, the patients are automatically removed from the cohort so that the operational teams continue to focus only on relevant patients.
2. Set To Come In (TCI) date before end of March 2023 for patients in the 78w cohort with a DTA:
The “admitted patients” cohort is another simple filter within the tool. This cohort can be further filtered by the wait time to view the 78w cohort, which flags patients without a TCI date. The list can be prioritised by TCI dates so that those with a date beyond the end of March 2023 can be prioritised for earlier treatment.
3. Validate all patients waiting over 52 weeks:
We have developed several algorithms to support the administrative cleansing of lists. These support technical, administrative, and clinical validation laid out in the toolkit and guidance published in December 2022. These algorithms include the ability to identify deceased patients, flag multiple entries, identify patients who do not have properly assigned intended procedures, and highlight patients with priority codes or whose condition has improved or deteriorated. Patient cohorts can then be contacted by the trust, using the latest contact details in the tool, to further validate condition and need for treatment.
4. Track progress and identify, validate, and cleanse duplicate entries:
By using standardised feeds, the waiting list tool will support tracking and the national reporting requirements. Furthermore, there is an inbuilt ability to identify and review duplicate entries. Algorithms identify patients with multiple entries (including those who are booked for the same procedure at multiple trusts), and patients with similar procedures booked which can then be easily operationally validated and clinically reviewed. In one trust, we identified that up to 16% of the entries on the waiting list were duplicates.
5. Correctly code choice patients:
Where the data is available, choice patient codes can be surfaced to ensure that patients are correctly coded.
6. Track and manage patients utilising independent sector capacity:
The tool integrates data about a patient across multiple care settings regardless of where treatment is being carried out using independent sector capacity. This enables clinical and operational teams to view and manage their patients where they are moving between providers, and report based on a multi-provider view. The tool can also help to increase the utilisation of capacity in the private sector through automatic identification of lower risk patients who, following clinical validation, can be offered treatment in independent sector hospitals.
In addition to this, there are algorithms developed to highlight various risks associated with patients on the waiting list which may need to be managed before, during and after treatment. This helps operational and clinical teams focus their efforts, highlighting patients who may need additional engagements to be ready for their TCI data and reducing the likelihood of cancellations.
The tool has the flexibility to utilise the national Waiting List Minimum Data Set (WLMDS) or waiting list data direct from source EPRs so that there can be a “plug and play” approach to realising the benefits from the tool, and significantly reducing the need to develop any additional data requirements beyond what exists already.